A Novel Immune-Related ceRNA Network and Relative Potential Therapeutic Drug Prediction in ccRCC

SLC11A1 predicts the overall survival of patients with colorectal cancer

Colorectal cancer (CRC) remains a significant contributor to cancer-related mortality, emphasizing the critical need for identifying biomarkers that can improve clinical management and patient outcomes. In this retrospective study, we analyzed tumor samples from 25 patients with metastatic CRC, categorized based on long-term (> 50 months) or short-term (< 10 months) survival. Employing the PanCancer Immune Profile Panel, encompassing 770 genes, in the discovery dataset, we identified 54 differentially expressed genes (DEGs) within the tumor microenvironment of metastatic CRC. Validation of potential biomarkers was performed using two publicly available RNA-based sequencing datasets (TCGA 1 (n=371) and TCGA 2 (n=566)). Univariate COX regression unveiled that three significant biomarkers were associated with overall survival in CRC within the discovery dataset, which were SLC11A1 (hazard ratio (HR): 4.09, P=0.012), TNFSF11 (HR: 3.67, P=0.02), and MEF2C (HR: 0.34, P=0.037). Kaplan-Meier survival curve analyses confirmed the correlation between SLC11A1 expression and overall survival in CRC across the discovery set (P=0.0071) and the two independent datasets (TCGA 1 (P=0.0016) and TCGA 2 (P=0.025)). Receiver operating characteristic curve analysis demonstrated an area under the curve ranging from 0.64 to 0.76, with sensitivity of 59% to 87% and specificity of 60% to 73% for predicting CRC overall survival. Immunohistochemistry staining further validated the strong expression of SLC11A1 protein in CRC tumor cells, with high expression correlating with short-term survival. These findings suggest that SLC11A1 serves as a predictive biomarker for overall survival in CRC patients.

Downregulation of RNA binding protein 47 predicts low survival in patients and promotes the development of renal cell malignancies through RNA stability modification

RNA binding proteins (RBPs) are crucial for cell function, tissue growth, and disease development in disease or normal physiological processes. RNA binding motif protein 47 (RBM47) has been proven to have anti-tumor effects on many cancers, but its effect is not yet clear in renal cancer. Here, we demonstrated the expression and the prognostic role of RBM47 in public databases and clinical samples of clear cell renal carcinoma (ccRCC) with bioinformatics analysis. The possible mechanism of RBM47 in renal cancer was verified by gene function prediction and in vitro experiments. The results showed that RBM47 was downregulated in renal cancers when compared with control groups. Low RBM47 expression indicated poor prognosis in ccRCC. RBM47 expression in renal cancer cell lines was reduced significantly when compared to normal renal tubular epithelial cells. Epithelial-mesenchymal transition (EMT) and transforming growth factor-β signaling pathway was associated with RBM47 in ccRCC by Gene set enrichment analysis. RBM47 expression had a positive correlation with e-cadherin, but a negative correlation with snail and vimentin. RBM47 overexpression could repress the migration, invasion activity, and proliferation capacity of renal cancer cells, while RBM47 inhibition could promote the development of the malignant features through EMT signaling by RNA stability modification. Therefore, our results suggest that RBM47, as a new molecular biomarker, may play a key role in the cancer development of ccRCC.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

SGMS1-AS1/MicroRNA-106a-5p/CPT2 Axis as a Novel Target for Regulating Lactate Metabolism in Colon Cancer

PURPOSE

The malignant transformation of cells can lead to aerobic glycolysis, an important form of metabolic reprogramming in colon cancer cells, which can cause the accumulation of lactate and accelerate the proliferation of tumor cells also enhance their chemotherapy drug resistance. The aim of this study was to investigate the possible molecular mechanisms responsible for the increased lactate expression in colon cancer.

METHODS

Several bioinformatics methods, including differential analysis, gene ontology enrichment, univariate and multivariate Cox regression analysis were used to find the lactic acid-related gene carnitine palmitoyltransferase 2. We analyzed the relationship between carnitine palmitoyltransferase 2 and clinical features as well as immune microenvironment. To further explore the mechanism of carnitine palmitoyltransferase 2 in colon cancer, we performed methylation analysis and constructed a competitive endogenous RNA network, which was validated in cell lines and clinical specimens.

RESULTS

We used bioinformatics to select the lactic acid-related gene carnitine palmitoyltransferase 2 and found low expression of carnitine palmitoyltransferase 2 was associated with poor prognosis in colon cancer. An inhibitory tumor microenvironment was created when carnitine palmitoyltransferase 2 expression was reduced, with decreased CD4 T cells, CD8 T cells, dendritic cells, and B cells but increased cancer-associated fibroblasts. Methylation analysis showed that the abnormal decrease in carnitine palmitoyltransferase 2 might be caused by hypermethylation. We constructed a network of SGMS1-AS1/microRNA-106a-5p/carnitine palmitoyltransferase 2 and verified their expression in cell lines and clinical specimens.

CONCLUSION

Our work revealed the possible mechanism of lactate accumulation in colon cancer and explored a new potential treatment for colon cancer by cutting off aerobic glycolysis in tumor cells.

Comprehensive analysis of immune ferroptosis gene in renal clear cell carcinoma: prognosis and influence of tumor microenvironment

OBJECTIVE

We conducted an in-depth study of the immune system and ferroptosis to identify prognostic biomarkers and therapeutic targets for renal clear cell carcinoma.

METHODS

Immune ferroptosis-related differentially expressed genes (IFR-DEGs) were selected from The Cancer Genome Atlas (TCGA). A lasso-Cox risk scoring model was established; its prognostic value was determined using prognostic analysis and single multivariate Cox analysis. Model genes were subjected to subcellular fluorescence localization, mRNA and protein expression analyses, and single-cell RNA sequencing localization analysis. Risk score was analyzed using the immune score, immune infiltrating cell correlation, immune checkpoint, TIDE, and drug sensitivity.

RESULTS

A total of 103 IFR-DEGs were identified; a risk model comprising ACADSB, CHAC1, LURAP1L, and PLA2G6 was established. The survival curve, single multivariate Cox regression, and receiver operating characteristic (ROC) curve analysis showed that the model had good predictive ability (p < 0.05). It was also validated using the validation set and total cohort. Subcellular fluorescence localization revealed that ACADSB, CHAC1, and PLA2G6 were distributed in the cytoplasm and LURAP1L in the nucleus. The mRNA and protein expression trends were consistent. Single-cell RNA sequencing mapping revealed that ACADSB was enriched in distal tubule cell clusters. In the Kidney renal clear cell carcinoma (KIRC) mutation correlation analysis, 1.56% of the patients were found to have genetic alterations; The Spearman correlation analysis of model gene mutations showed that ACADSB was positively correlated with LURAP1L, which may have a synergistic effect; it was negatively correlated with CHAC1 and PLA2G6, and CHAC1 was negatively correlated with LURAP1L, which may have an antagonistic effect. Model and immune correlation analyses found that high-risk patients had significantly higher levels of CD8+ T cells, regulatory T cells (Tregs), immune checkpoints, immune scores, and immune escape than those in low-risk patients. High-risk patients had a higher susceptibility to small-molecule drugs.

CONCLUSION

A novel prognostic model of immune ferroptosis-related genes (ACADSB, CHAC1, LURAP1L, and PLA2G6), which plays an important role in immune infiltration, microenvironment, and immune escape, was constructed. It effectively predicts the survival of patients with KIRC.

Up-regulation of SLC27A2 suppresses the proliferation and invasion of renal cancer by down-regulating CDK3-mediated EMT

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of the urinary system. Distant metastasis is the leading cause of poor prognosis in ccRCC. However, ccRCC is found poorly responsitive to radiotherapy and chemotherapy. Effective therapeutic strategies for its metastasis remain scarce. We analyzed clinical samples and public database, for differential expression of SLC27A2 and further explored its relationship with clinical prognosis. Biochemistry and functional experiments were carried out to study the potential mechanisms of SLC27A2, CDK3, and EMT. SLC27A2 was significantly downregulated in clinical specimens and renal cancer cell lines and predicted poor prognosis. We found that specific upregulation of SLC27A2 could significantly inhibited the proliferation, migration, and invasion of renal cancer cell lines. SLC27A2 could also influence the Epithelial-mesenchymal transition (EMT) signaling pathway, linked to the progression and metastasis of renal cancer. Using whole transcriptome sequencing of SLC27A2, CDK3 was identified as a regulatory SLC27A2 target. In terms of mechanism, SLC27A2 may further inhibit the epithelial-to-mesenchymal transition by negatively regulating CDK3. Our work suggests that functional inhibition of SLC27A2-CDK3-EMT axis may be an attractive therapeutic target for metastasis of ccRCC.

Transmembrane Transporter Sema3D Serves as a Tumor Suppressor in Localized Clear Cell Renal Cell Carcinoma

Background

The transmembrane transporter Sema3D is a vital molecule involved in axon guidance and carcinogenesis of variant malignancies. However, the relationship between Sema3D and clear cell renal cell carcinoma (ccRCC) is barely reported and remains unclear.

Methods

Sema3D expression and the connection of clinical and histological characteristics were first analyzed with transcriptome data in the TCGA repository. We then located and examined the Sema3D expression in ccRCC patients by using immunofluorescence staining in the tissue microarray. The prognostic value of Sema3D in localized ccRCC was evaluated by Cox proportional hazard analysis. Functional and gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to describe the potential mechanisms of Sema3D in ccRCC. Correlation analysis between Sema3D and tumor-infiltrating lymphocytes was calculated by ssGSEA.

Results

In 86 ccRCC patients, Sema3D mRNA and protein expression were downregulated in tumor tissues than the para-tumor tissues, and Sema3D was dominantly expressed in the extracellular space. Low expression of Sema3D was associated with advanced tumor stage, advanced histological grade, and poor prognosis in ccRCC. In the subgroup analysis of 81 localized ccRCC patients, Sema3D expression level was an independent protective prognostic factor for overall survival (OS) (HR = 0.125, p=0.043). Coagulation, complement, estrogen response, and KRAS signaling hallmark gene sets were identified as Sema3D-related signaling pathways. The expression level of Sema3D was significantly correlated with a high abundance of several immune cells (neutrophils, eosinophils, and T helper cells).

Conclusions

Transmembrane transporter Sema3D is an efficient prognostic biomarker for localized ccRCC patients, by playing the role of tumor suppressor in ccRCC. Sema3D can be a novel therapeutic target for ccRCC.